Ernest Davis

This book takes a look at the current state of development of Artificial Intelligence (AI). As one would expect, it is laid out in a logical manner. It traces the history of AI and what has (and has not) been achieved to date. The authors believe that AI is not as far advanced as many people believe, primarily due to a tendency for published articles and headlines to exaggerate accomplishments. A major premise is that AI needs to be trustworthy and safe, and currently falls short of this goal. Areas that need attention are language comprehension, situational awareness, and common sense.

“Statistics are no substitute for real-world understanding. The problem is not just that there is a random error here and there, it is that there is a fundamental mismatch between the kind of statistical analysis that suffice for translation and the cognitive model construction that would be required if systems were to actually comprehend what they are trying to read.”

“If we could give computers one gift that they don’t already have, it would be the gift of understanding language.”

The authors are intentionally trying to reach a wider audience than solely those already familiar with AI progress to date and its terminology. There may be a few terms that need to be looked up depending upon the reader’s background. Chapters include:
1 – The mind gap
2 – What’s at stake
3 – Deep learning and beyond
4 – If computers are so smart, how come they can’t read?
5 – Where’s Rosie?
6 – Insights from the human mind
7 – Common sense and the path to deep understanding
8 – Trust

The authors suggest that we need to move beyond Deep Learning (solving problems through bigger neural networks and larger data sets) and toward building cognitive models. Of course, it is not easy to develop a more robust AI. This book presents evidence that indicates a dramatic shift is needed, arguing that doing more of what we have done in the past is not going to achieve a breakthrough.

There are many examples provided. It may be too detailed for many “general interest” readers but will definitely appeal to techies or non-techies that want to understand AI’s shortcomings and potential. Leaders in the business world would benefit from reading this book.

Bottom line: we have made amazing progress but still have a long way to go.

“Trustworthy AI, grounded in reasoning, commonsense values, and sound engineering practice, will be transformational when it finally arrives, whether that is a decade or a century hence … And the best way to make progress toward that goal is to move beyond big data and deep learning alone, and toward a robust new form of AI — carefully engineered, and equipped from the factory with values, common sense, and a deep understanding of the world.”
… (mais)

The book reflects a belief I've been having for some time now, mainly that we are currently barking up the wrong tree when it comes to AI.
We are making amazing tools, thats certain, but most people see the latest improvements in solving a very specific problem and extrapolate from that to believe we are close to having a general purpose AI, or True AI.

It compares classical AI with modern ML driven AI and talks about the strengths and weaknesses of both. Modern AI is amazing, but the flawed classical AI with all of it's impracticality is the only way we can ever achieve AGI, not by improving neural networks or making ML more efficient.

My belief is that when it comes to developing true AI we need to go back to the drawing board and classical AI is better at helping achieve it than the modern approaches that are being overhyped by Media with hyperboles, clickbait and in some cases fraud. If you share this belief than you'll enjoy this book.… (mais)